Robust self‐scheduling of a virtual multi‐energy plant in thermal and electricity markets in the presence of multi‐energy flexible technologies

摘要

Summary Virtual power plant (VPP) aggregates a diverse set of renewable energy sources, energy storages, and flexible loads to operate them as a single power plant in the energy markets. With the advent of multi‐energy systems, the operation and mechanism of traditional VPPs are enhanced for acting in multiple markets and providing more flexibility for energy management systems. In this work, a robust optimization method is proposed for optimal self‐scheduling of a new VPP termed as a virtual multi‐energy plant (VMEP) in electricity and thermal markets in the presence of different energy storages. The proposed VMEP consists of wind turbines, heat‐only units, combined heat and power units, photovoltaic panels, electrical energy storages, and thermal storages. Also, thermal and electrical price‐based demand response (DR) programs are employed to shift the multi‐carrier energy demand of the VMEP's consumers into low price periods. In addition, a robust decision‐making model is implemented to deal with the uncertainty of electricity market prices in the optimal self‐scheduling of the VMEP without the need for a probability distribution function. The simulation results demonstrate that the implementation of multi‐energy DR programs can increase the VMEP's daily profit by about 8.5%. Additionally, the economic performance of the VMEP in multi‐energy markets is enhanced up to 10.5% by utilizing multi‐carrier energy storages.